1. Technical Field
Present invention embodiments relate to query processing data processing systems, and more specifically, to execution of queries using a dimension table implemented as decompression dictionaries to reduce or eliminate join operations.
2. Discussion of the Related Art
Data is often organized into tables that are divided into rows and columns. In a denormalized database schema, fact tables may contain columns of data that represent quantities of interest while dimension tables may contain values that provide categories of data. For example, if a fact table such as a “sales” table contains separate sales figures for each month and for each product, then details of months and products may be stored in “month” and “product” dimension tables.
Small dimension tables are fairly common in a denormalized database schema. These small dimension tables require a join operation to be carried out in order to take advantage of dimension filtering against a fact table. Solutions such as semi-joins, Materialized Query Tables (MQTs), and materialization of one or more dimension columns into the fact table (reversing the schema denormalization) are solutions that are either in use today or proposed solutions to provide higher performance for predicate filtering that occurs from local predicates applied to the dimension then joining the dimension to the fact table. Each of these increase disk space usage, or introduce various maintenance issues and/or overhead.